Software Testing Checklist: What Belongs on It, Phase by Phase
This software testing checklist groups every item by the phase of the test process it belongs to, marks the items teams routinely skip, and shows how to wire the lis…
DevOps and Release Automation
for AWS and Azure
Pipeline design, environment automation and release orchestration for AWS and Azure teams, with testing built into every stage. We automate how code is built, tested and shipped, so releases stop depending on one person and a long weekend.
150+ clients
450+ projects
275+ engineers
15+ years
ISO/IEC 17025:2017Accredited testing laboratory
CMMI Maturity Level 3The process is written down and repeats
ISO 9001:2015Quality management
ISO/IEC 27001Information security
What We Automate
Three layers, one team: the pipeline, the infrastructure under it and the containers it ships.
CI/CD Pipelines
Automated build, test and deploy with GitOps, on Jenkins, GitHub Actions, GitLab CI, AWS CodePipeline or Azure DevOps. Unit, integration, security and UI tests run on every change.
Infrastructure as Code
Environments defined in Terraform and Ansible with enforced policies, so staging matches production and drift shows up as a failed check, not a failed release.
Containers and Orchestration
Containerised services on Docker and Kubernetes, packaged with Helm and released through ArgoCD, with auto-scaling set to real load.
If a release needs a war room, the pipeline is the problem.
Free Environment ReviewRelease Problems We Fix
The four failures that slow most teams down, and what replaces each one.
Manual Deployments
Error-prone manual steps replaced by automated pipelines with rollback controls built in.
Infrastructure Drift
Inconsistent environments brought back in line with infrastructure as code and enforced policies.
Slow Release Cycles
Long feedback loops cut with unit, integration and smoke tests running on every build.
No Ops Visibility
Blind spots closed with Prometheus and Grafana dashboards and real-time alerts routed to an owner.
Testing Built Into Every Stage
We are a testing lab first, so quality gates are designed in, not bolted on once the pipeline works.
Commit
Unit tests and static analysis run before a merge, so broken code never reaches the main branch.
Build
Integration and contract tests on every build. A red build stops the line and names an owner.
Pre-Release
Security scans and UI regression in a production-like environment. Account-level checks run through cloud security testing.
Release and After
Smoke tests after every deploy, automatic rollback on failure and alerts to the team on call.
Results From Delivery
Regulated and high-traffic systems, built and tested by the same team that automates their releases.
Two private-sector banks · Lending platforms
Loan processing and agent onboarding rebuilt for two leading private-sector banks, with the compliance each engagement required. Platforms like these change through tested, repeatable releases, not manual deploys.
60% faster loan processing50% less agent onboarding timeDiagnostics Chain Back End
The back end for a Chennai diagnostics chain, built to carry the integrations and load that real patient volume produces.
Cybersecurity SaaS
A cybersecurity SaaS product tested under DDoS simulation, so the team knew how it fails and recovers before its customers did.
How an Engagement Starts
Value in weeks, not quarters, starting with one environment.
Environment Review
A free review of one environment: how you build, test and release today, and where time is lost.
Pipeline Plan
Target pipeline, tools, quality gates and rollout order, written down. A full workflow audit runs through DevOps consulting and CI/CD.
First Pipeline
A working pipeline for your first service, typically within 4 to 6 weeks, with release time and failure rate measured.
Scale or Hand Over
Extend to more services, train your team to run it, or hand day-two operations to managed cloud services.
Why Teams Choose Vervali for DevOps
Pipelines built by people who test for a living, on the stack you already run.
Testing Lab Discipline
An ISO/IEC 17025 accredited lab with CMMI Level 3 process, so every gate in your pipeline is designed, documented and repeatable.
Tool Agnostic
AWS, Azure or hybrid, Jenkins or GitHub Actions. We work with your stack, and plan the bigger moves through cloud consulting and strategy.
An Extension of Your Team
Working hours overlap 9am to 1pm Eastern with delivery from India, and the team scales up or down as releases demand.
Frequently Asked Questions
Cloud testing checks how an application behaves in the cloud environments it actually runs in: functional, load, security, failover and configuration tests against AWS, Azure or Google Cloud. In a DevOps setup those checks run inside the pipeline, so every release is tested in a production-like environment before it ships, rather than in a separate test phase weeks later.
The five most often named are Amazon Web Services, Microsoft Azure, Google Cloud, Alibaba Cloud and Oracle Cloud, with IBM Cloud close behind. Most of our DevOps work runs on AWS and Azure, and we write pipelines and infrastructure as code that can target more than one provider when your estate needs it.
Common choices include JMeter and k6 for load, Selenium, Playwright and Cypress for UI, Postman for APIs, OWASP ZAP for security, and BrowserStack or AWS Device Farm for device coverage. The tool matters less than where it runs. We wire these into Jenkins, GitLab CI, GitHub Actions or Azure DevOps so they run on every build.
UAT is run by business users, so the tools focus on tracking rather than scripting. Teams commonly use Jira or Azure DevOps for test cases and defects, TestRail or Zephyr for test management, and screen capture tools for feedback. In a DevOps pipeline we automate the checks before UAT, so business users spend their time on real acceptance decisions.
A DevOps consultant reviews how your team builds, tests and releases software, then designs and puts in the improvements: CI/CD pipelines, infrastructure as code, containers, monitoring and the quality gates in between. A good one leaves your team able to run it without them. Most of our engagements start with a free review of one environment.
No. AI is changing DevOps, not replacing it. It now helps write pipeline code, flag risky changes and sort alerts, but someone still has to design the release process, own production access and decide when to roll back. Teams that combine AI assistance with solid pipelines and testing ship faster than teams relying on either one alone.
Yes. Teams still need fast, safe releases, matching environments and cloud costs under control, and those needs grow as more workloads move to AWS and Azure. Demand has shifted toward platform engineering, security in the pipeline and observability, which is where most of our DevOps engagements now focus alongside the core CI/CD work.
The 7 C’s usually describe the DevOps lifecycle: continuous development, continuous integration, continuous testing, continuous deployment, continuous feedback, continuous monitoring and continuous operations. Each one shortens the time between writing code and learning how it behaves in production. Our pipelines cover all seven, with continuous testing as the stage we take most seriously.
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